Is Analytical Precision Always Necessary? Redefining Real-Time Monitoring Towards Smart Wastewater Treatment Plants

Smart wastewater treatment plants are increasingly essential for improving the resilience of water infrastructure under climate-related disturbances and operational variability. Despite significant advances in sensing technologies and data analytics, full-scale automation remains limited. One of the primary barriers is that monitoring strategies remain primarily designed for regulatory compliance, prioritizing absolute analytical accuracy often at relatively high cost, thereby limiting their widespread use for real-time decision-making. This perspective proposes a shift from compliance-oriented monitoring to purpose-oriented monitoring, in which monitoring systems are designed according to the operational purpose they support. To support this shift, we introduce a framework recognizing that different operational applications require different levels of measurement performance. Accordingly, compliance assessment, early warning, process troubleshooting, real-time control, and asset management each require different combinations of accuracy, precision, temporal resolution, and tolerance to measurement error. Within this framework, high-frequency multi-source data streams from conventional, spectral, visual, and virtual sensors can provide complementary information on process dynamics, effectively supporting operational decisions, even when individual measurements do not achieve laboratory-level analytical performance. When combined with hybrid models that integrate mechanistic and data-driven approaches, this purpose-oriented monitoring framework can enable predictive process management and accelerate the transition toward autonomous wastewater treatment systems.